Adaptive interference suppression based on an invariant subspace of matrices matching for a horizontal array in underwater acoustics.

Passive detection of target-of-interest (TOI) within strong interferences poses a challenge. This paper introduces an adaptive interference suppression based on an invariant subspace of matrix matching. Assume that the TOI-bearing intervals are known.

Analysis of under-ice ambient noise characteristics of Gakkel Ridge in the Arctic.

This paper presents an analysis of the under-ice acoustic data and environmental parameters measured over a three-month period from August 31 to November 28, 2021, within the area of the Gakkel Ridge in the Arctic. After "spikes" caused by micro-level events are removed, the distribution of the retained under-ice noise related to macro-level events can be described satisfactorily by a Gaussian distribution, as verified by Q-Q plots and kurtosis/skewness analysis. We use sliding window analysis to deal with the features of under-ice ambient noise and model the data by Gaussian interpolation.

High-resolution frequency-difference beamforming for a short linear array.

Conventional beamforming (CBF) is a commonly employed approach for detecting and estimating the direction-of-arrival (DOA) of acoustic signals in underwater environments. However, CBF becomes ambiguous due to spatial aliasing when the received signal's half wavelength is smaller than the array spacing. Frequency-difference beamforming (FDB) allows for processing data in the lower frequency Δf without encountering spatial aliasing by utilizing the product of array data at frequency f with its complex conjugate at frequency f+Δf.

Ambient noise under stably covered ice.

Sea ice and freshwater ice can be different in terms of physical and acoustic characteristics, such as density, salinity, etc. In this paper, under-ice ambient noise in the Mudan river (Jilin Province, Northeast of China) is analyzed using the data recorded by autonomous hydrophones to test if the river ice environment is an effective analog for studying under-ice noise of multi-year ice sheets in the Arctic. The noise spectrum level below 250 Hz and above 1 kHz decreases linearly with the increase in the logarithmic frequency in a quiet environment.

A Bioinspired Twin Inverted Multiscale Matched Filtering Method for Detecting an Underwater Moving Target in a Reverberant Environment.

To this day, biological sonar systems still have great performance advantages over artificial sonar systems, especially for detection in environments with clutter, strong reverberation, and a low signal to noise ratio (SNR). Therefore, mammal sonar systems, for instance, bats and toothed whales, have many characteristics worth learning from. This paper proposes a bioinspired twin inverted multiscale matched filtering method to detect underwater moving targets.

Multitarget Tracking Algorithm Using Multiple GMPHD Filter Data Fusion for Sonar Networks.

Multitarget tracking algorithms based on sonar usually run into detection uncertainty, complex channel and more clutters, which cause lower detection probability, single sonar sensors failing to measure when the target is in an acoustic shadow zone, and computational bottlenecks. This paper proposes a novel tracking algorithm based on multisensor data fusion to solve the above problems. Firstly, under more clutters and lower detection probability condition, a Gaussian Mixture Probability Hypothesis Density (GMPHD) filter with computational advantages was used to get local estimations.

Effects of low-order atmosphere-turbulence aberrations on the entangled orbital angular momentum states.

Based on Zernike-model expansion of turbulence phase aberrations and non-Kolmogorov spectrum model of index-of-refraction fluctuation, we analyze the effects of low-order Zernike turbulence aberrations on orbital angular momentum (OAM) entanglement states in a weak fluctuation region. The signal photon detection probability of OAM entanglement states propagating in a slant turbulence channel with non-Kolmogorov turbulence Z-tilt, defocus, astigmatism, and coma aberrations are modeled, respectively. The results demonstrate that turbulence Z-tilt aberration is the dominant aberration, coma is the second, and astigmatism is the third, but that the defocus aberration has no impact on the detection probability.